We prove that if NP ⊆ BPP, i.e., if SAT is worst-case hard, then for every probabilistic polynomial-time algorithm trying to decide SAT, there exists some polynomially samplable ...
Abstract. Many real-time embedded systems involve a collection of independently executing event-driven code blocks, having hard real-time constraints. Portions of such codes when t...
Samarjit Chakraborty, Thomas Erlebach, Lothar Thie...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
Existing profile-guided partial redundancy elimination (PRE) methods use speculation to enable the removal of partial redundancies along more frequently executed paths at the expe...